1-2-1-MNVTON: Efficient images, virtual trying on of clothes by people in videos (to be opened)

General Introduction

1-2-1-MNVTON is an open source project based on GitHub, which aims to achieve efficient virtual try-on through "Modality-specific Normalization for Virtual Try-On" (MNVTON) technology. The project solves the problem of high computational cost of traditional virtual try-on technology, and provides a high-quality and efficient try-on experience.MNVTON technology through the modality-specific normalization process, making the virtual try-on more realistic and accurate, suitable for e-commerce platforms, fashion industry and other need for virtual try-on scenarios.

Function List

• Efficient Virtual Try-On: Through MNVTON technology, it realizes efficient and realistic virtual try-on effect.
• Open source code: Provide complete open source code for developers to carry out secondary development and application.
• High-quality output: Generate high-quality virtual try-on images to enhance user experience.
• Calculation Cost Optimization: Optimize the calculation cost to make the virtual try-on more efficient.
• Modal Normalization: Improve the accuracy of the fitting effect through the normalization of specific modes.

Using Help

Installation process

1. Clone the project code:

   git clone https://github.com/ningshuliang/1-2-1-MNVTON.git

2. Go to the project catalog:

   cd 1-2-1-MNVTON

3. Install the dependencies:

   pip install -r requirements.txt

4. Run the project:

   python main.py

Instructions for use

1. Efficient virtual fitting: After running the program, users can upload their photos and pictures of the garments they want to try on, and the system will automatically generate virtual fitting results.
2. open source: Developers can modify and extend the code according to their needs for different application scenarios.
3. high definition output: The virtual try-on images generated by the system are of high quality and can be directly downloaded and shared by users.
4. Computational cost optimization: By optimizing the algorithm, the consumption of computational resources is reduced, making the virtual fitting process more efficient.
5. modal normalization: The system improves the accuracy and realism of the virtual fitting effect through modality-specific normalization.

Detailed Operation Procedure

1. Upload photos: Users first need to upload a photo of themselves and a picture of the garment they want to try on.
2. Select Modal: The system will automatically select the appropriate modality for normalization based on the images uploaded by the user.
3. Generate fitting results: The system automatically generates virtual try-on results that users can preview and adjust.
4. Download and share: Users can download the generated high-quality fitting results locally or share them directly to social media.